6 research outputs found

    Automatic Vehicle Tracking System Based on Fixed Thresholding and Histogram Based Edge Processing

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    Automatic detection, extraction and recognition of vehicle number plate region in traffic control systems is one of the prominent application in Computer vision. The drastic increase in number of vehicles in the current generation greatly increases the complexity in tracking the vehicles through the human visual system, manual procedure of controlling traffic and enforcement of various laws and rules is not sufficient for smooth control of traffic. This urges the need for development of technology that can automate this process. This paper mainly focuses on the development of an automatic number plate extraction and recognition algorithm by incorporating constructs like edge detection, horizontal and vertical edge processing using fixed threshold technique. The extracted number plate region is again processed using template matching algorithm for the recognition of the characters embossed on the number plate with respect to every individual piece of number plate. The algorithm developed has achieved an accuracy of around 100% and works for both front and rear images of the car

    A New Approach for Recognizing Saudi Arabian License Plates using Neural Networks

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    In this paper, a neural networks (NN) based automatic license plate recognition system (ALPR) is proposed for Saudi Arabian license plates with Arabic characters. The license plate region is rst localized by rst tracing the exterior and the interior close boundaries of objects in the car image and then separating the license plate by determining the rectangularity characteristic of these close objects. Character segmentation is performed via vertical and horizontal projection proles. Finally, a Multilayer Feedforward Neural Network (MFNN) with a backpropagation (BP) algorithm is used for character recognition. We discuss new features from the characters for training the NN. The results obtained from a medium size data base are very promising, i.e., 98%. The alogoritms discussed here were tested at the entrance of a praking lot to mimic a real life situation

    Identification of Saudi Arabian License Plates

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    Identification of Saudi Arabian License Plates

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    Identification of Saudi Arabian License Plates

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